Natural language (or ordinary language) is any language which is the result of the innate facility for language possessed by the human intellect. A natural language is typically used for communication, and may be spoken, signed, or written. For people, the understanding of natural languages reveals much about how language works (e.g., language syntax, semantics, etc.). Electronic databases may store vast amounts of information, which is only useful with an effective search function. Certain technological constructs may be created to translate natural language semantics with stored data relationships in order to provide user search requests with relevant results from the stored data.
A semantic network is a network that represents semantic relations among terms (e.g., concepts). A semantic network may be used as a form of knowledge representation, and therefore may be used to model business knowledge in companies and their various parts, e.g. as enterprise knowledge and/or terminology.
The typical usage may be in search engines, where the network may be used within different techniques to identify the meaning of the term and/or sentence. Mainly the search terms are defined as words in some order or relation. The searched term may then be interpreted by the search engine as a string/term. For example, the search result for “Lotus” may be divided into results about “Lotus” as a model of a car, “Lotus” as a brand of car oil, and “Lotus” as a flower. In this situation, there are different knowledge domains. The knowledge domains can be ordered hierarchically, which allows for knowledge grouping, e.g. the first two meanings may belong to similar knowledge groups, and the last one has nothing in common and is defined in a completely different context/knowledge group (e.g., as a flower).
The natural language distinguishes between different parts of speech and therefore grammarians, e.g., writers of dictionaries, reflect this in the structured terminology catalogues, e.g., dictionaries. One part of the common sentence is the lexical word which is composed of nouns, verbs, and adjectives. Composition of sentences are addressed in the field of linguistics of language syntax; i.e., focus on compositionality in order to explain the relationship between meaningful parts and whole sentences. Therefore, syntax is the study of the principles and rules for constructing sentences in natural language. Further, in language theory, we can see many different “constructs” that try to reflect the language syntax, e.g., define language grammar. An example may include Relational Grammar (RG), e.g., syntactic theory which argues that primitive grammatical relations provide the ideal means to state syntactic rules in universal terms. Another example may include Role and Reference Grammar (RRG), e.g., the description of a sentence in a particular language is formulated in terms of (a) its logical (semantic) structure and communicative functions, and (b) the grammatical procedures that are available in the language for the expression of these meanings. Several other grammatical theories and examples exist, such as: Arc Pain Grammar (APG), Generalized Phrase Structure Grammar (GPSG), Hard-Driven Phrase Structure Grammar (HPSG), and Lexical-Functional Grammar (LFG).
The thematic relation is a term used to express the meaning that a noun (or noun-phrase) plays with respect to the verb, i.e. the action or state described by a sentence's verb. From another perspective, the semantic network is a network which represents semantic relations among terms (concepts). The semantic network is used as a form of knowledge representation and therefore is very often used to model business knowledge in companies and its parts, e.g. as enterprise knowledge/terminology.
The semantic network allows for creation of terms—phrases that are defined by types which characterizes/specifies the particular term (though, a term may be assigned to different types). Additionally, the term may be used in different knowledge areas and may have different (or slightly different) meaning for each area. The knowledge domains may be ordered hierarchically, which allows for knowledge grouping. Therefore, some modeling solutions are used to define context of particular terms/information.
A knowledge domain may group terms that belong to the same subject or expertise area, for example IT, finance, etc. The knowledge/expertise area may be grouped into knowledge domains and may then be used to specify the context of the required information and deliver data with better quality. Typically, the business knowledge and used terminology is distributed through the whole company via the jargon used by company experts and in the many documents associated with the company. The main problem is how to share the currently used business terminology to simplify business communication, e.g. providing phrase/term suggestions in composing documents, like mail, documentations, marketing documents and flyers, etc. Additionally, the same business knowledge (in the form of a business semantic network) may be reused in other business areas, e.g., searching for business information/documents/data.